MODELING, SIMULATION AND SIZING OF A MICROGRID IN THE

PAN-AFRICAN UNIVERSITY

INSTITUTE FOR WATER AND ENERGY SCIENCES

(Including CLIMATE CHANGE)

Master Dissertation

Submitted in partial fulfillment of the requirements for the Master degree in

ENERGY ENGINEERING

Presented by

Somia BECHLAGHEM

Defended on 08/11/2020 Before the Following Committee:

Chair Prof. Mohammed Osman Sid Ahmed SUST, Khartoum, Sudan

Supervisor Prof. Zahera DIB University of Tlemcen

External Examiner Prof. Leila GHOMRI University of Mostaganem

Internal Examiner Prof. Souhila BENSMAINE University of Tlemcen

MODELING, SIMULATION AND SIZING OF

A MICROGRID IN THE UNIVERSITY CAMPUS

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PAN AFRICAN UNIVERSITY - INSTITUTE OF WATER AND

ENERGY SCIENCES (INCLUDING CLIMATE CHANGE)

ENERGY ENGIGNEERING

MASTER THESIS DRAFT PLAN

TOPIC:

MODELING, SIMULATION AND SIZING OF

A MICROGRID IN THE UNIVERSITY CAMPUS

CASE STUDY: CHETOUANE, TLEMCEN, ALGERIA

NORTH AFRICA

SUPERVISOR: PROF. Zahera DIB

PREPARED BY: Somia BECHLAGHEM

SUPERVISOR STUDENT

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STATEMENT OF THE AUTHOR

I Somia BECHLAGHEM, hereby declare that this thesis represents my personal work, realized

to the best of my knowledge. I also declare that all information, material and results from other

works presented here, have been fully cited and referenced in accordance with the academic

rules and ethics.

STUDENT SUPERVISOR

Somia BECHLAGHEM Dr. Zahera DIB

Academic Unit: Energy (Engineering Track) University of Tlemcen

PAU Institute: PAUWES

Date: 11 /2020

SIGNATURE SIGNATURE

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DEDICATION

To my parents,

who have always stood by my side

To my sister and brothers,

for their love and support

To all my friends,

for all the motivation and help that they had given me

I dedicate this work.

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ACKNOWLEDGEMENT

I would like to express my gratitude and appreciation to all those who have given me the

opportunity to complete this work. I would like to take this opportunity to express my deepest

gratitude to the African Union Commission for giving me to be part of the Pan African family.

I would like to thank those who have provided help and support during the preparation of this

work. I am grateful to my supervisor Madam Zahera DIB, who has devoted a lot of effort and

assistance during this whole journey. Special thanks go to Mr. N. ZERHOUNI and Mrs. L. CHIALI

for their valuable efforts, support, and guidance.

I am forever grateful for all of those who provided support, comments, and reviews on this

work.

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ABSTRACT

The current power grid is one of the most complex engineering systems in the world.

Electricity generation in the traditional power grid is very centralized, where energy is

delivered unidirectionally from power plants to end-users via a transmission network.

With a worldwide increase in population and thus in electricity demand, the technical

problems as well as the environmental concerns associated with fossil fuel combustion have

stimulated research to develop new technologies for more sustainable, reliable, and efficient

energy systems. With the emergence of Distributed Energy Resources as Solar, wind, biomass,

etc., smart microgrids are gradually being recognized as a solution for various problems in the

current power system especially for remote regions and well-defined loads as university or

military campuses. Using renewable energy sources along with the traditional power

generators, also energy storage, and controlling the energy usage are some of the novel

aspects of smart microgrids.

The purpose of this study is to propose a modeled and simulated design of a DC microgrid for

a localized area in the “university campus of Chetouane”. The system is grid-connected and

can provide energy autonomously using solar panels, with a backup supply of batteries and a

diesel generator.

The research results will be valuable to the energy management sector and related decision-

makers in developing better tools for sustainable and cost-effective energy. This study focuses

on the adoption of a decentralized hybrid electricity system in Algerian universities and goes

hand in hand with the government's objective to diversify its energy mix as well as going

towards achieving SDG's and global targets.

Keywords: DC Microgrid, renewable energies, distributed energy, PV, energy storage

system, Diesel generator, Simulink MATLAB, PVsyst, energy management system, grid

connected mode, island mode

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RÉSUMÉ

Le réseau électrique actuel est l'un des systèmes d'ingénierie les plus complexes au monde.

La production d'électricité dans le réseau électrique traditionnel est très centralisée, l'énergie

étant acheminée de manière unidirectionnelle des centrales électriques aux utilisateurs finaux

via un réseau de transmission.

Avec l'augmentation de la population mondiale et donc de la demande d'électricité, les

problèmes techniques ainsi que les préoccupations environnementales liés à la combustion

des combustibles fossiles ont stimulé la recherche pour développer de nouvelles technologies

pour des systèmes énergétiques plus durables, plus fiables et plus efficaces. Avec l'émergence

des ressources énergétiques distribuées comme le solaire, l'éolien, la biomasse, etc., les

micro-réseaux intelligents sont progressivement reconnus comme une solution à divers

problèmes du système électrique actuel, en particulier pour les régions éloignées et les

charges bien définies comme les campus universitaires ou militaires. L'utilisation de sources

d'énergie renouvelables en plus des générateurs d'électricité traditionnels, le stockage de

l'énergie et le contrôle de l'utilisation de l'énergie sont quelques-uns des nouveaux aspects

des micro-réseaux intelligents.

L'objectif de cette étude est de proposer une conception modélisée et simulée d'un micro-

réseau à courant continu pour une zone localisée dans le "campus universitaire de

Chetouane". Le système est connecté au réseau et peut fournir de l'énergie de manière

autonome à l'aide de panneaux solaires, avec une alimentation de secours par batteries et un

générateur diesel.

Les résultats de la recherche seront précieux pour le secteur de la gestion de l'énergie et les

décideurs concernés, car ils permettront de mettre au point de meilleurs outils pour une

énergie durable et rentable. Cette étude se concentre sur l'adoption d'un système électrique

hybride décentralisé dans les universités algériennes et va de pair avec l'objectif du

gouvernement de diversifier son bouquet énergétique ainsi que d'atteindre les objectifs de la

SDG et les objectifs mondiaux.

Mots-clés : Micro-réseau DC, énergies renouvelables, énergie distribuée, PV, système de

stockage d'énergie, générateur diesel, Simulink MATLAB, PVsyst, système de gestion de

l'énergie, mode connecté au réseau, mode îlot.

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TABLE OF CONTENTS

COVER PAGE….................................................................................................... . STATEMENT OF AUTHOR….................................................................................... . DEDICATION....................................................................................................... . ACKNOWLEDGEMENT............................................................................................ ABSTRACT.......................................................................................................... . RESUME............................................................................................................. TABLE OF CONTENTS.............................................................................................. LIST OF FIGURES................................................................................................... LIST OF TABLES.................................................................................................... .. LIST OF ABBREVIATIONS........................................................................................ .

1. INTRODUCTION............................................................................................... . 1.1. Background of the research project .................................................................... 1.2. Problem Statement ...................................................................................... . 1.3. Aim and Objectives ...................................................................................... . 1.4. Methodology ............................................................................................. . 1.5. Justification ................................................................................................ 1.6. Scope and Limitations ................................................................................... . 1.7. Conclusion ................................................................................................ .

2. LITERATURE REVIEW......................................................................................... . 2.1. Introduction................................................................................................ 2.2. Related works ............................................................................................ . 2.3. Algeria Overview...........................................................................................

2.3.1. Economy vs. Energy in Algeria ..................................................................... 2.3.2. Energy production.................................................................................. .. 2.3.3. Energy consumption................................................................................ . 2.3.4. Electricity............................................................................................. 2.3.5. Renewable Energy .................................................................................. 2.3.6. Policy and renewable energy in Algeria .......................................................... 2.3.7. Renewable energy consumption in Algeria ...................................................... 2.3.8. Solar Energy ..........................................................................................

2.4. Microgrids ................................................................................................. . 2.4.1. The microgrids concept............................................................................. 2.4.2. Microgrid composition............................................................................. . 2.4.3. Microgrid classification............................................................................. . 2.4.4. Microgrid and distributed generation ............................................................

2.4.4.1. Characteristics and concepts .............................................................

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2.4.4.2. PHOTOVOLTAICS .......................................................................... 2.4.4.3. Diesel Generator ......................................................................... . 2.4.4.4. ENERGY STORAGE........................................................................ .. 2.4.4.5. Battery .....................................................................................

2.4.5. Microgrid Monitoring .............................................................................. . 2.5. Smart grids ................................................................................................ .

2.5.1. In What Ways Are Smart Grids ‘‘Smarter’’? ..................................................... .

2.5.2. Sensing and Measurement in Smart Grid.......................................................... 2.5.3. Next Generation Smart Communication Subsystems in SGs.................................... 2.5.4. Conclusion........................................................................................... ..

3. METHODS ..................................................................................................... . 3.1. Introduction.......................................................................................... ...... 3.2. Research Approach Overview……..................................................................... ..

3.2.1. Study assumptions................................................................................. .. 3.2.2. Research procedure.................................................................................. 3.2.3. Software Based Approach ..........................................................................

3.3. Step 01: Demand side management..................................................................... 3.3.1. Building description ............................................................................... .. 3.3.2. Analysis of energy consumption ...................................................................

3.4. Step 02: Supply-side management..................................................................... .. 3.4.1. System configuration.............................................................................. .. 3.4.2. System sizing ........................................................................................

3.4.2.1. Geographical site…....................................................................... .. 3.4.2.2. Natural resources assessment and weather data...................................... 3.4.2.3. Defining Solar system components ......................................................

3.5. Step 03: Simulation and control........................................................................ . 3.5.1. Load profile....................................................................... ..................... 3.5.2. PV block............................................................................................. .. 3.5.3. Storage system block ............................................................................... 3.5.4. Diesel generator block .............................................................................. 3.5.5. Global configuration of the microgrid.............................................................

3.6 Step 04: Analysis ................................................................................... ....... 3.7 Conclusion ........................................................................................... ......

4 RESULTS AND DISCUSSION ................................................................................ .. 4.1 Introduction ............................................................................................... ... 4.2 Step 01: Demand-side management ...................................................................... 4.3 Step 02: Supply-side management..................................................................... ... 4.4 Step 03: Simulation and control........................................................................ ....

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4.4.1 PV .................................................................................................... 4.4.2 Battery ............................................................................................... 4.4.3 Microgrid ........................................................................................ ....

4.5 Step 04: Analysis................................................................................... ....... 4.5.1 Economic analysis of PV system................................................................... 4.5.2 Environmental analysis of PV system.............................................................

4.6 Conclusion…..........................................................................................

5 SUMMARY, CONCLUSIONS & PERSPECTIVES …………………………………………….……………..

6 REFERENCES ………………………………………………………………………………………………………

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LIST OF FIGURES

Figure 2.1: Algeria’s map .............................................................. 11

Figure 2.2: Algeria’s Localisation..................................................... 11

Figure 2.3: Total primary energy supply............................................. 12

Figure 2.4: Algeria's Energy Consumption by Fuel Source.................... 13

Figure 2.5: Electricity generation in Algeria......................................... 16

Figure 2.6: Solar insolation Map of the World................................... 16

Figure 2.7: Global horizontal irradiation............................................

For Algeria 17

Figure 2.8: PV power potential in Algeria............................................ 17

Figure 2.9: Typical structure of a microgrid......................................... 19

Figure 2.10: Structure of a DC microgrid.............................................. 22

Figure 2.11: Structure of an AC microgrid............................................. 23

Figure 2.12: Structure of an AC/DC microgrid........................................ 23

Figure 2.13: Structure of independent PV system.................................... 25

Figure 2.14: Structure of grid-connected PV power................................. 26

Figure 2.15: Typical genset efficiency curve.......................................... 28

Figure 2.16: The main components of the future smart grid....................... 30

Figure 2.17: Smart grid environment within the broader electricity system...... 33

Figure 2.18: The future smart Grid and its application.............................. 34

Figure 2.19: Smart cities and IoT....................................................... 36

Figure 3.1: Wind potential assessment in Chetouane.............................. 39

Figure 3.2: Solar potential assessment in Chetouane.............................. 40

Figure 3.3: Research approach overview............................................ 40

Figure 3.4: PAUWES building.........................................................

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Figure 3.5: GPS localization of PAUWES ............................................

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Figure 3.6: System configuration ....................................................

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Figure 3.7: Building’s Surface estimate..............................................

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Figure 3.8: Panels orientation........................................................

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Figure 3.9: System’s simplified sketch...............................................

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Figure 3.10: Defining the site’s geographical position..............................

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Figure 3.11: Solar paths at Chetouane................................................ 47

Figure 3.12: Relation of I-V/P-Vo f PV cell at different light intensities........... 49

Figure 3.13: Relation of I-V/P-Vo f PV cell at different Temperatures............ 50

Figure 3.14: Load profile modelling …................................................

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Figure 3.15: PV model block............................................................ 54

Figure 3.16: Daily irradiation for May,11th 2020 .................................... 54

Figure 3.17: Battery model block...................................................... 55

Figure 3.18: Diesel generator model block........................................... 56

Figure 3.19: General block of the microgrid .......................................... 56

Figure 3.20: Algorithm control in case of PV availability ............................ 57

Figure 3.21: Algorithm control in case of PV non availability ....................... 57

Figure 4.1: Daily load curve for both a working and a weekend day............. 61

Figure 4.2: Daily average consumption per part for a working day.............. 61

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Figure 4.3: Daily average consumption per part for a weekend day............. 62

Figure 4.4: Yearly average consumption per part.................................. 62

Figure 4.5: Daily consumption by appliance for a working day................... 63

Figure 4.6: Yearly Distribution of consumed energy ............................... 63

Figure 4.7: Yearly Distribution of produced energy ............................... 64

Figure 4.8: Loss diagram............................................................... 65

Figure 4.9: Simulation result for PV power in a sunny day......................... 66

Figure 4.10: Simulation result for PV power in a sunny day with a shading....... 66

Figure 4.11: Simulation results for batteries charging mode....................... 67

Figure 4.12: simulation results for batteries discharging mode.................... 67

Figure 4.13: simulation results for the microgrid..................................... 68

Figure 4.14: Income allocation on the project life................................... 69

Figure 4.15: balance of CO2 emissions................................................ 70

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LIST OF TABLES

Table 2.1 Algeria's Electricity generation......................................... 14

Table 2.2 Targets, Policies and Measures........................................ 15

Table 2.3 Algeria's renewable energy Consumption........................... 15

Table 2.4 Data on solar radiation in Algeria...................................... 17

Table 2.5 Classification of microgrids by capacity................................... 21

Table 2.6 DOE Seven characteristics of a Smart Grid............................... 32

Table 3.1 Input data for the research................................................ 38

Table 3.2 Output data of the research...............................................

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Table 3.3 Weather data for Chetouane.............................................. 48

Table 3.4 PV System sizing and characteristics .....................................

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Table 3.5 Inverter’s characteristics................................................... 51

Table 3.6 Battery’s characteristics...................................................

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Table 3.7 genset’s characteristics.................................................... 52

Table 3.8 Economical Data for analysis.............................................. 58

Table 4.1 Detailed economic results (USD) ......................................... 69

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LIST OF ABBREVIATIONS

SDG Sustainable Development Goals MENA Middle east and North Africa DC Direct Current AC Alternative Current PV Photovoltaic GDP Gross Domestic Product DER Distributed Energy Resources DG Distributed Generation ES Energy Storage ESS Energy Storage Systems CHP Combined Heat and Power DES Distributed Energy Sources CCHP Combined Cooling and Heating Power DR Distributed Resources MPPT Maximum Power Point Tracking CAES Compressed Air Energy Storage SMES Super-conducting Magnetic Energy Storage PQ Power Quality SG Smart Grids HEMS Home Energy Management System BEMS Building Energy Management System AMI Advanced Metering Infrastructure IoT Internet of Things O&M Operation and Maintenance LCOE Levelized Course of Energy

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CHAPTER 1. INTRODUCTION

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1.1 Background of the research project

A series of profound inequalities characterize the world of energy. According to the Energy

Access Outlook 2019 [1], nearly one billion people worldwide (13% of the global population)

continue to be left in the dark with no or limited access to electricity. More than two-thirds

represent people living in sub-Saharan Africa, mainly in rural and remote areas, while

affording efficient and cost-effective electricity for all is one of the most SDG’s priorities. Also,

the disparity between the expectations of a rapid renewable energy drive transition and the

reality of today’s energy system relying obstinately on fossil fuels. It is worth mentioning the

existence of another gap between the latest scientific evidence underlining the need to reduce

global greenhouse gas emissions faster than ever before and the data showing that today

energy-related emissions have hit a record high (40% higher than emissions in 1990) [2].

The international community is increasingly recognizing the major environmental problems

caused by human activities. The World Energy Council is an international organization that

supports the development of accessible and sustainable energy worldwide. It stresses the

importance of taking into account energy security, energy equity, and environmental

sustainability. Thus, the energy transition involves a radical change in energy policy [3].

In 2000, 817 million Africans made up just over 13 % of the world's population; by 2018, that

percentage had risen to about 17 %, bringing Africa's population to nearly 1.3 billion, more

than double the global growth rate [1].

With such growth, access to modern energy is a central pillar to reduce poverty and sustain

Africa's economic growth. That can be achieved through expanding energy production

capacity (on-grid and off-grid) and energy sources diversification switching to more

sustainable and green energy. Regardless of the abundant renewable energy sources, Africa

holds from solar to wind, biomass, and hydro to geothermal energy. These sources have not

been exploited due to the limited policies and lack of investment financing.

Algeria is holding the first place in Africa in terms of surface size, with a desert covering 80%

of its area. Its geographic location represents an excellent potential for renewable energy

sources, especially solar energy. The significant economic transformations that have been

witnessed in recent years globally have made it necessary for Algeria to undertake structural

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changes to gradually adapt to these changes, particularly in the energy sector. By promoting

the use of renewable energy technologies for power generation, and targeting a share of 27%

of renewables in the energy mix by 2030 [4], Algeria is aiming to reduce its reliance on fossil

fuels.

The modern electrical grid is one of the most complex engineering systems. In the traditional

power grid, power generation is highly centralized, with energy moving unidirectionally from

generators to end users via a transmission/distribution network. However, conventional

power utilities' technological and environmental problems have boosted research and

development of new technologies for energy systems. With the emergence of distributed

energy resources, e.g., wind, photovoltaics, batteries, fuel cells, etc., microgrid technologies

as an effective way to integrate renewable distributed generation into power systems have

attracted increasing attention [5]. Microgrids can control distributed generation efficiently,

flexibly, and smartly [6]. Therefore, it can best improve reliability, costs reduction, and

enhance the efficiency of the electrical system [3].

1.2 Problem Statement

Recently, the electric power system is facing a radical transformation worldwide. With the

population growth and the pressure on the national power grids, energy production is moving

towards centralized power stations by adopting microgrids.

Microgrid deployments are expanding in the world’s power systems, and they are very

interesting solutions to supply autonomous power to particular loads such as university

campuses, hospitals, or military bases. University campuses were among the early adopters

of microgrids for many reasons, specifically for their large and well-defined loads.

In Algeria, providing free education and accommodations, university campuses and

dormitories are supplied with electricity from the primary centralized grid. However,

demographic rhythms impose severe limits and weigh heavily on existing grids.

According to Eco MENA [7], based on its geographical location, Algeria contains an enormous

solar energy potential in the world with an estimation of 13.9 TWh per year. The annual

sunshine exposure in Algeria is equivalent to 2,500 KWh/m2. Daily solar energy potential

varies from 4.66 kWh/m2 in the north to 7.26 kWh/m2 in the south.

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With such potential, the government is seeking to harness by launching an ambitious

renewable energy and energy efficiency program.

The program aims to produce 22,000 MW of energy using renewable energy resources

between in a period between 2011 and 2030, with more than 12,000 MW destined for

domestic consumption while the rest for export. The program focuses on the development

and increased use of renewable resources such as solar, wind, biomass, geothermal, and

hydropower to diversify reliable energy sources and promote sustainable development of the

country [7].

In order to achieve these targets, and tackle the environmental and economic problems

related to the reliance on fossil fuels, adopting microgrids in remote areas and public

construction and buildings can best meet these requirements.

1.3 Aim and Objectives

This study aims to propose a modeled and simulated design of a DC microgrid for a localized

area in the “University Campus of Chetouane” which is the PAUWES building. An off/on-grid

hybrid system that will rely on PV power generation with a backup of diesel generator and

batteries.

The objective is therefore to design, study, analyze and develop a direct current (DC) microgrid

that integrates photovoltaic (PV) sources, which are the most common renewable energy

sources for urban and rural areas. This system should be capable of extracting the maximum

power from the photovoltaic panels and manage the transfer of energy to the load while

taking into account the connection to the public grid, available storage units and other back-

up source represented by a diesel generator. The ultimate goal is to achieve, through

intelligent control, an optimized local production-consumption of electricity, in secure mode,

with a controlled injection of power while taking into account the fluctuations in metrological

parameters.

Our study will target the following question:

How can the challenges related to the operation and control of the microgrid system be

addressed and what are the proposed solutions?

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This research results will be valuable to the energy management sector and related decision-

makers in developing better tools and projects for sustainable and cost-effective energy. This

study is about adopting hybrid decentralized power system in Algerian universities and goes

along with the government's aim to diversify its energy mix to reach the energy target plan

2030.

1.4 Methodology

To achieve our objective, our research has proceeded through the following steps:

• Step 01: Demand-side management by evaluating the campus’ existing energy

infrastructure. Because of the COVID-19 pandemic, it was impossible to perform a

walkthrough energy audit; therefore, for collecting data regarding the energy performance

of the building and forecasting the load profile, our estimation was based on a previous

valid audit performed by a group of students in 2019.

• Step 02: Supply-side management, the first thing to be done in this stage was to collect

the metrological data as solar radiation and temperature, in addition to reviewing and

studying the operation of microgrid system. And finally, sizing the system using PVsyst, by

assessing the geographical position, implementation surface, and Market choices/prices.

• Step 03: Simulation and control Using Simulink MATLAB, the system is simulated and

modeled in different scenarios and with several conditions and cases.

• Step 04: at the end, Financial, Environmental, Analysis were conducted to see how

effective the system is and its impact on both energy savings and environmental protection.

1.5 Justification

Our hybrid system, composed of PV panels with batteries and a diesel generator, is a reliable

university campus solution that reduces energy reliance on the primary grid. This solution can

be extended to other well-defined load constructions and especially in remote areas. This

study is very relevant for improving access to electricity in African rural regions.

Moreover, this work is of significant importance for Algeria as It will help reduce the high

dependence on conventional energy sources (primarily gas) and contribute to strengthening

low-cost and environmentally friendly energy supply.

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1.6 Scope and Limitations

Not all the complex characteristics of the hybrid microgrids can be studied in a single research

project; hence this master thesis focuses only on a specific target case study: sizing, modeling,

and simulation of a DC microgrid within the particular building of the university campus of

Chetouane.

Because solar energy is abundant at the location where the case study is being undertaken,

Photovoltaic power was selected in preference to wind power. Besides, many recent projects

and investments are being carried out in the field of solar energy worldwide.

Diesel generators are the best-known conventional power generators used in remote sites.

Yet, using a fossil fuel generator limits the switch to more clean energies.

Furthermore, adding an energy storage system makes the power generated hard to be a price

competitive to the grid power, giving the fact that batteries are the most expensive part of

the system.

1.7 Conclusion

This chapter provided an overview about the problem statement and the targeted objectives

of the current study. Given the short history of microgrid and being a relatively new research

domain, many technologies are still under test. With researches on this area going deeper, the

subsequent chapter explores the literature providing an overview about our topic.

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CHAPTER 2. LITERATURE REVIEW

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2.1 Introduction

This chapter provides the key insights from the history of related projects and works

conducted in the research topic. Also, it includes an overview about Algeria where our case

study occurs, followed by a deep dive into the different aspects of microgrids and electrical

networks.

2.2 Related works

A microgrid, as a concept, was originated in The United States [6]. Today, microgrids are very

often proposed in energy distribution networks, and this increased use can undoubtedly

change the traditional topology of the system. DC micro-grids are expected to provide energy

efficiency. There is a lot of research on different aspects of microgrids; those studies vary from

one application to another. On the other hand, the main research issues in the field of

microgrids are related to energy quality and management, operational safety,

communication, control, and economics. However, system control, protection, and energy

management seem to be the most important ones [3].

In 2001, Professor R.H. Lasseter from the University of Wisconsin-Madison first proposed a

"micro-network" concept. In the meantime, the Consortium for Electric Reliability Technology

Solutions (CERTS) and the Micro-Grid project of the European Commission also provided their

definitions of a micro-grid.

In 2002, the National Technical University of Athens (NTUA) set up a small laboratory

microgrid project known as the NTUA Power System Laboratory Facility for tests on

distributed resource and load monitoring with multi-agent technology.

Since 2003, numerous pilot projects have been undertaken worldwide, including the 7.2 kV

microgrid at Mad River Park in Vermont USA, the 400 V microgrid on the Kythnos Islands in

Greece, and the Aichi, Kyotango, and Hachinohe projects in Japan.

Nowadays, many universities, research institutes, and large companies carry out studies on

the microgrid and have set up demonstration projects [6].

Authors in [8] investigated microgrid structures and reviewed campuses’ case studies in

different universities in the world. Starting from USA universities, The University of California,

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San Diego (UCSD) with 42 MW microgrid; Illinois Institute of Technology, Chicago, with 20 %

of the load supplied by the microgrid; New York University, New York with 13.5 MW microgrid

capacity and other universities. The article moves to Europe, presenting The University of

Central Lancashire, the UK with 300 kW capacity, The University of Genoa, Italy with 250 kW

of electricity auto-generation, the Technical University of Denmark with 36 kW power

capacity. Furthermore, the authors reviewed other case studies in both Thailand, China, and

Turkey universities.

Marina Elenkovaet al. presented in [9] a simulation platform for smart microgrid configuration

in the Democritus University of Thrace (DUTH) in Greece. The micro-grid cited includes

photovoltaic, energy storage units, and load management schemes by analyzing the actual

power consumption.

In [10], a control strategy for energy management is proposed by a scheduling algorithm for

the optimal operation of a microgrid and its real-time application. The results show the

benefits of the suggested programming to make optimal and harmonious use of the adopted

microgrid, even in varying transitions between grid-connected and island modes.

A microgrid based on wind and solar energy sources was also proposed in [11], where the

authors discuss issues related to the system's functioning, control, and stability. Thanks to

Matlab/Simulink, the system was modeled and simulated to identify relevant technical

problems associated with microgrid operation based on renewable energy production units.

In [12] Chanaka Keerthisinghe and al. evaluated a microgrid planned to be installed by

Snohomish PUD in Arlington, WA, using a real-time digital simulation on an OPAL-RT real-time

digital simulator. This model allows the study of different operating conditions before

deploying the microgrid at field by the end of 2021. Once the microgrid is operational, the

authors will compare the actual simulations with real measured data.

Considering that our research work is carried out in Algeria, and according to the

bibliographical survey taking Algeria as a case-study, a lack of investigations related to our

subject also underlines our research's importance and significance.

Three main relevant works were reviewed, starting from [13], where the researchers

proposed a first conception of a microgrid in the Sahara area, which includes diesel, wind, and

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solar energy. Thanks to MEGASIM of the RT-LAB platform, the model was applied in real-time

simulation. The obtained results facilitate the understanding of microgrid's operation in terms

of power flow and default responses.

In Algeria’s same region, the authors in [14] presented a DC microgrid for agricultural farms in

Adrar zone. The microgrid modules were illustrated using the distributed energy resources

and power converters' mathematical and equivalent circuits. The DC microgrid was then

evaluated using MATLAB Simulink and ETAP software to study both the transition and the

steady-state parameters.

A very relevant case study for our research was conducted in [15], where the analyses

presented an estimation of photovoltaic energy potential in the USTO campus located in Oran

city. In addition to that,[16] provides a comparison between the output of photovoltaic and

energy consumption in the university of USTO. The solar photovoltaic energy produced is

analyzed taking into account economic aspects such as the cost of investment and the annual

cash flow from energy production. The installed capacity of the photovoltaic system has been

calculated, and the energy produced is estimated. The feasibility analysis shows an internal

rate of 5% return, a payback period of 10.3 years, and a profitability index of 1.78.

2.3 Algeria Overview

Algeria, a large North African country of nearly 2.4 million km2[17]. From the Mediterranean

coast, where the majority of its population lives, Algeria stretches southwards into the heart

of the Sahara, a hostile desert where the highest surface temperatures on the planet have

been recorded and which makes up more than four-fifths of the country's surface area (more

than two million km2). The Sahara and its extreme climate dominate the country.

Algeria is bordered to the east by Tunisia and Libya; to the South by Niger, Mali, and

Mauritania; to the west by Morocco and Western Sahara; and to the North by the

Mediterranean Sea. It is a vast country - the largest in Africa and the Arab world and the 10th

largest in the world [18] between the 38°-35° of latitude north and 8°-12° longitude east. The

northernmost region, generally known as Tell, is subject to the Mediterranean's moderating

influences and consists mainly of the Atlas Mountains, which separate the coastal plains from

the second region to the South. This southern region, which is almost entirely desert, makes

11

up most of the country's territory and is located in the Sahara's western part, which stretches

across North Africa. On the other hand, its 1,200 km of coastline gives it a strategic continental

position in the Maghreb heart.

Four factors clearly outline Algeria's future potential: the country's geographical qualities, its

demographic composition, its oil wealth, and its modern and experienced security sector.

Algeria is also a demographic power with 43.8 million (in May 2020) [17]. Its capital, the most

populous city, is Algiers, located in the North of the country. Administratively, Algeria is

divided into 48 provinces called Wilayas.

Algeria is one of the largest energy-producing and exporting countries in the world. This has

been achieved by implementing strategies and policies to promote energy resources'

economic, social, and environmental use.

2.3.1. Economy vs. Energy in Algeria

Algeria, the third most important economy in the MENA region and a leader in the Maghreb,

is one of the many countries that have achieved a 20 percent reduction in poverty over the

past two decades. Indeed, the Algerian government has taken significant steps to improve its

people's well-being by implementing social policies in line with the UN Sustainable

Development Goals.

Figure 2.1. Algeria’s map [19] Figure 2.2. Algeria’s Localisation [20]

12

The Algerian economy is highly dependent on hydrocarbons and world oil and gas prices. GDP

growth reached 1.5% in 2018, compared with 1.4% the previous year, and remained at 1.5%

in the first quarter of 2019. Growth in the hydrocarbon sector was slow, with economic activity

contracting by 6.5% in 2018 and 7.7% in the first quarter of 2019, partially offsetting the slight

increase in non-hydrocarbon growth of 3.4% 3.9%, respectively [21].

The government's 2016-2019 economic plan reduces its exposure to crude oil price volatility

by diversifying its exports (hydrocarbons represent more than 90% of total exports in 2016)

and reducing the growth of its domestic energy consumption (of which hydrocarbons are the

primary source of fuel) to 3% in 2030 [22].

2.3.2. Energy production

Algeria's energy production is dependent on conventional (oil and gas) and renewable energy

sources. Algeria's energy production has increased over the past few decades to meet

household, industrial and transport demands.

Figure 2.3. Total primary energy supply [23]

13

2.3.3. Energy consumption

According to the latest estimates provided by the BP 2018 Statistical Review of World Energy,

Algeria's domestic energy consumption was about 2.11 quadrillion British thermal units in

2017. Algeria mainly uses oil or oil products and natural gas to meet domestic demand. Only

a small fraction of domestic consumption comes from coal, hydroelectricity, and renewable

energies. Algeria does not have significant nuclear, hydroelectric, coal, or renewable energy

capacity [24].

2.3.4. Electricity

Algeria's electricity production capacity reached around 19 gigawatts (GW) in 2016. Electricity

consumption was about 56 billion kilowatt-hours (kWh) in Algeria in 2016, double what it was

ten years ago. Most of the production capacity comes from natural gas power plants and

combined cycle power plants. The share of renewable energies in the Algerian production park

is increasing but remains limited.

According to the World Bank Group's latest estimates, 99% of the Algerian population has

access to electricity, with around 100% in urban areas, and 98% in rural areas. Although

extensive and serving almost the entire population, Algeria's transport and distribution

systems have experienced relatively high losses, 15.9% in 2016 [24].

Figure 2.4. Algeria's Energy Consumption by Fuel Source, 2017 [24]

14

2.3.5. Renewable Energy

In recent years, political support for renewable energy has grown steadily, both nationally and

internationally. Most scientists now agree that the Middle East and North Africa are well

placed to play a leading role in the future's lucrative solar and wind energy industries. Algeria

plays a vital role in world energy markets, both as a significant producer and exporter of

hydrocarbons and a critical player in the renewable energy market. Because of its geographical

situation, Algeria has been considered one of the best countries for exploiting solar energy.

Algeria benefits from a relatively high level of sunshine, moderate solar radiation, and wind

speed, as well as biomass energy resources.

2.3.6. Policy and renewable energy in Algeria

Algeria adopted in 2011 a strategy whose objective is to produce 40% of its electricity from

renewable resources by 2030. But it has been reduced to 27% in reality after the revision of

the new program in 2015 [27].

Table 2.1. Algeria's Electricity generation [23]

15

When we look at the issue of renewable energies in Algeria, we can see that the country has

the technological means, both financial and human, to develop this sector. However, we

quickly realize that it lacks the essential: the political will. The least that can be said is that the

country has several constraints that rely mainly on oil and gas. Algeria has a window of a few

years to put in place a policy of voluntarism based on energy sobriety. Like the developed

countries, an audacious strategy must be put in place. An energy mix of 50% renewable

energies. Therefore, it is important to set up an energy transition that will enable it to reduce

its dependence on fuels by reserving oil for noble uses only, saving energy, and launching the

energy plan without delay.

2.3.7. Renewable energy consumption in Algeria

Thanks to its geographical location and its strategic position in the energy sector, all the

conditions are in place for Algeria to play a crucial role in the future supply of green electricity,

following the Trans-Mediterranean Plan.

Table 2.2. Targets, Policies and Measures [24]

Table 2.3. Algeria's renewable energy Consumption [24]

16

2.3.8. Solar Energy

In all the Mediterranean basins, there is a gigantic reservoir of solar energy in North Africa,

particularly in Algeria's southern region. With average annual sunshine of 2000 h and

evaluated on a territory composed of 86% of the Sahara Desert, its solar energy is estimated

at 1700 KWh/m2/year in the North and 2650 KWh/m2/year in the South, which corresponds

to capacity eight times higher than the country's natural gas reserves and the largest solar

fields in the world [25].

Figure 2.6. Solar insolation Map of the World [25]

Figure 2.5. Electricity generation in Algeria [24]

17

The history of the use of solar energy in Algeria goes back to 1954 with the French's solar

furnace for the manufacture of ceramics. The insulation time over almost the entire national

territory can exceed 2000 hours per year and reach 3900 hours (high plains and Sahara). The

daily energy obtained on a horizontal surface of 1 m² is 5 KWh over most of the national

territory, i.e., about 1700 KWh/m²/year for the North and 2263 KWh/m²/year for the South

of the country (table 00 and figure 00).

Region Coastal Highlands Sahara

Area (%) 4 10 86 Average sun hours per year

2650 3000 3500

Energy received KWh/m2/year

1700 1900 2650

The amount of solar radiation in Algeria means that it would be possible to consider solar

energy as a potential energy source for different applications in the form of individual

photovoltaic solar panels or systems. Photovoltaic solar energy is developed in Algeria mainly

for six applications: domestic uses, water pumping, refrigeration, village electrification,

lighting, and telecommunications. The Ministry of Energy and Mines supports solar power

plants' development and is mainly carried out by Sonelgaz and other private installation

companies. Solar energy is considered an important research area within the structure of the

Sonelgaz Renewable Energy Department. The UDTS/CDTA (Silicon Technology Development

Table 2.4. Data on solar radiation in Algeria [25]

Figure 2.7. Global horizontal irradiation

For Algeria [26]

Figure 2.8. PV power potential in Algeria [26]

18

Unit, in collaboration with the Centre for the Development of Advanced Technologies) in

Algiers, is working on developing solar cells. With encapsulation, the procedure workshop

allows 250 KW/year up to 500 KW/year. A polycrystalline silicon growth furnace with 25

ingots/year capacity, in the first phase, allows the elaboration of silicon ingots. Facilities for

cutting silicon ingots and equipment for electrical, optical, and structural evaluation are also

available. The manufacture of PV modules at ENIE (National Company of the Electronic

Industry) is limited to mono and polycrystalline silicon solar cells, the assembly of PV modules,

and the manufacture of the supporting structure. The UDES/CDER (Solar Equipment

Development Unit in collaboration with the Centre for the Development of Renewable

Energies) ensures the development of solar thermal and photovoltaic equipment (domestic,

industrial, and agricultural), electronic, thermal, and mechanical devices and systems involved

in the application of solar energy. This means that establishing a silicon production industry is

possible in Algeria to supply the local, MENA, and European markets [27].

2.4 Microgrids

2.4.1 The microgrids concept

Traditionally, the power and energy flow in on direction from larger generators through a

network of transmission and distribution to the users, making the power generation in the

grid highly centralized.

The development and research of new power system is stimulated with the several technical

issues related to the traditional electrical utilities and the environment.

Microgrid technologies have attracted attention as a good way for the integration of DER

unites to the power systems used for the different distributed energy sreources (DER) such as

PV, biomass, battery, fuel cell and micro-turbine [27].

A microgrid is a single, controllable, independent power system comprising distributed

generation (DG), load, energy storage (ES), and control devices, in which DG and ES are directly

connected to the user side in parallel [6].

The definition of a microgrid from the European Technology Platform of Smart Grids, is an

integrity facilitating platform for, energy storage systems ESS, distributed generators (DG),

19

and loads in order a sustainable delivery of power from the grid with a reliable electricity and

competitive prices.

Figure (2.9) shows a typical microgrid structure, comprising DGs, such as combined heat and

power unit (CHP), micro-turbines, PV systems, wind power systems, fuel cells; distributed

energy storage (DES) facility such as battery banks, super-capacitors, flywheels, electric

vehicles; flexible loads and control devices [27].

2.4.2 Microgrid composition

A microgrid is composed of distributed generation (DG), loads, energy storage (ES), and

control devices. It acts as a single entity with respect to the grid, and connects to the grid via

a single point of common coupling.

▪ DG: It can be various types of new energy, such as photovoltaic (PV), wind, and fuel

cell; or combined heat and power (CHP) or combined cooling, heat, and power (CCHP),

which provides heat for users locally, thereby increasing efficiency and flexibility of DG.

▪ Loads: It includes common load and critical load.

Figure 2.9. Typical structure of a microgrid

20

▪ ES: It includes physical, chemical, and electromagnetic forms, for storage of renewable

energy, load shifting, and black-start of microgrid.

▪ Control devices: They constitute the control system for DGs, ESs, and transfer between

grid-connected mode and islanded mode, facilitating real-time monitoring and energy

management [6].

2.4.3 Microgrid classification

Different types of microgrids should be established according to capacity, location, and types

of DRs to suit the local situation [6]. Microgrids can be classified as follows according to:

→ Demand

The classification of microgrids is done into simple microgrid, multi-DG microgrid, and utility

microgrid by function demand.

▪ Simple Microgrid

It contains a single type of distributed generation with a simple design and function with the

use of continuous supply or CCHP to loads.

▪ Multi-DG microgrid

It is composed of multiple simple microgrids or multiple types of complementary, coordinated

DGs. In comparison with the first type, it costs much more in terms of design, operation and

complication. In order to maintain power balance during emergencies to identify some loads.

▪ Utility microgrid

It contains all the distributed generation and other simple microgrids that meet specific

technical conditions. The priority is for loads depending on user’s reliability and requirement

with the powering of high priority loads in emergency cases.

Microgrids are classified by demand with the definition of the ownership during operation up

to operating and managing the simple microgrids by customers, while utility microgrids can

be operated via the utilities, and the multi distributed generators to be operated either by

utilities or customers.

21

→ Capacity

Microgrids are classified into simple microgrid, corporate microgrid, feeder area microgrid,

substation area microgrid, and independent microgrid by capacity, as shown in Table (2.5)

▪ Simple microgrid

A simple microgrid has a capacity below 2 MW and is intended for independent facilities and

institutes with multiple types of loads and of a small area, such as a hospital or school.

▪ Corporate microgrid

A corporate microgrid has a capacity of 2–5 MW, and comprises CCHPs of varying sizes and

some small household loads, generally no commercial or industrial loads.

▪ Feeder area microgrid

A feeder area microgrid has a capacity of 5–20 MW and comprises CCHPs of varying sizes and

some large commercial and industrial loads.

▪ Substation area microgrid

A substation area microgrid has a capacity above 20 MW and generally comprises common

CCHPs and all nearby loads (including household, commercial, and industrial loads). These four

types of microgrids are connected to common grids, and therefore, are collectively called grid-

connected microgrid.

▪ Independent microgrid

An independent microgrid is mainly intended for remote off-grid areas such as an island, a

mountainous area, or a village, and the distribution system of the main grid uses a diesel

generator or other small units to meet the power demand of such areas.

Table 2.5. Classification of microgrids by capacity

22

→ By AC/DC type

Microgrids are classified into DC microgrid, AC microgrid, and AC/DC hybrid microgrid.

▪ DC microgrid

As shown in Figure (2.10), in a DC microgrid, DG, ES, and DC load are connected to a DC bus

via a converter and the DC bus is connected to AC loads via an inverter to power both DC and

AC loads.

The advantages of the DC microgrid are as follows:

1. As DG control solely depends on DC voltage, it is easier to realize coordinated operation of

the DGs.

2. DG and load fluctuations are compensated by ES on the DC side.

3. Compared with an AC microgrid, a DC microgrid is easier to control, does not involve

synchronization among DGs, and thus is easier to suppress circulating current. The

disadvantage of the DC microgrid is that inverters are required for the power supply to AC

loads.

Figure 2.10. Structure of a DC microgrid

23

▪ AC microgrid

An AC microgrid connects to the distribution network via an AC bus, and the AC bus controls

the microgrid’s connection to and disconnection from the distribution network through the

circuit breaker at the PCC. Figure (2.11) shows the structure of an AC microgrid, in which DG

and ES are connected to the AC bus via inverter. The AC microgrid is a dominant type of

microgrid, and the major topic of this book in the following chapters. The advantage of the AC

microgrid is that as the microgrid is connected to the grid through an AC bus, no inverter is

required for power supply to AC loads. The disadvantage is that control and operation are

difficult.

▪ AC/DC hybrid microgrid

An AC/DC hybrid microgrid is a microgrid consisting of an AC bus and a DC bus. Figure (2.12)

shows the structure of such a microgrid, in which the AC bus and DC bus allow for direct supply

to AC loads and DC loads. With special power sources connected to an AC bus, an AC/DC hybrid

microgrid is essentially a special AC microgrid on the whole.

Figure 2.11. Structure of an AC microgrid

Figure 2.12. Structure of an AC/DC microgrid

24

2.4.4 Microgrid and distributed generation

2.4.4.1 Characteristics and concepts

Every small electric power system independent of traditional utility grids refers to Distributed

generation (DG), located on the side of the user in order to satisfied users demands. This

includes internal combustion engine, microturbine, fuel cell, small hydropower system,

photovoltaic (PV) generation, wind generation, waste generation, and biomass generation.

Distributed resource (DR) refers to a combined DG and energy storage (ES) system, that is,

DR = DG + ES. It includes all DG technologies and can store energy in a battery, flywheel,

regenerative fuel cell, superconducting magnetic storage device, and other devices.

Distributed energy resources (DER) mean generation of electricity or heat on the user side for

local use. It includes all DG and DR technologies, and systems connected to a utility grid with

which users can sell surplus power to utilities. As a definition it can refer to the DG as a subset

of DR which in its turn a subset of DER [6].

2.4.4.2 PHOTOVOLTAICS

PV is a means of electricity generation by directly converting solar energy to electricity. The

solar cell is the core component for light-to-electricity conversion. The worldwide market is

dominated by the crystalline silicon solar cell, and other types include amorphous silicon thin

film solar cell and compound thin film PV cell. A PV power system may operate independently

or in parallel with the grid [6].

▪ PV power with independent system

It is not connected to the traditional electric power system and its generally deployed in

remote off0grid areas to fulfill the local requirements. During the daytime the electrification

of PV is possible, with the requirement of power during all time. In order to solve the issue,

the presence of an independent PV systems is required with ES. Figure (2.13) shows the

structure of an independent PV power system, mainly consisting of solar cell array, DC

combiner box, controller, battery, off-grid inverter, and AC distribution box. The PV

components produce direct current to charge the battery and, after DC to AC conversion by

the inverter, serve the AC loads.

25

- Solar cell array: it consists of two or more solar cell modules fabricated by encapsulation of

solar cells. At present, single crystalline or polycrystalline silicon solar cells are used, which

are made of waterproof glass on the front contact and soft material on the back contact. It

is the most fundamental component of a PV power system for conversion of solar energy to

electricity. DC combiner box: Combines multiple circuits of low-current DC outputs of solar

cell array into one or more circuits of high-current outputs. Its output may then be collected

to the next-level combiner box or the inverter, and it can protect against and monitor the

occurrence of over-current, countercurrent, and lightning strike.

- Controller: Controls the charge and discharge voltage and current of the battery, balances

the energy of the system, collects system status information, and controls, protects, and

monitors the charge and discharge processes of ESs.

- Battery: Stores the intermittent and uncertain energy produced by solar cells to ensure

power supply balance and continuity.

- Off-grid inverter: Inverts direct current to alternating current to serve AC loads.

- AC distribution box: An enclosed or semi enclosed metal box housing

- AC-side switchgear, meters, protections, and other auxiliary equipment for ease of

maintenance and management.

Figure 2.13. Structure of independent PV system

26

▪ Grid-connected PV power system

A grid-connected PV power system is connected to the grid and injects electricity to the grid.

It is the mainstream of PV power systems. Grid-connected PV power systems can be further

divided into distributed type and centralized type. The former is a type of DG in a microgrid,

in which electricity is directly distributed to users and the surplus or deficit is regulated by the

grid. The latter is a PV power system that directly injects electricity to the grid for distribution

to users. The structures of these two types are essentially the same. Figure (2.14) shows the

structure of a grid-connected PV power system, mainly comprising solar cell array, DC

combiner box, DC distribution box, grid-tie inverter, and AC distribution box. Their functions

are the same as those of an independent PV power system. For the off-grid inverter and grid-

tied inverter, the similarity is that they both convert direct current to alternating current, and

the difference is that the former is the voltage source for U/f output and the latter the current

source for P/Q output. In addition, the grid-tied inverter has the following functions:

(1) maximum power point tracking (MPPT), that is, it always produces the maximum power

when the output voltage and current vary with the cell temperature and solar irradiance;

(2) output of current for harmonics suppression to ensure power quality of the grid;

(3) automatic tracking of voltage and frequency of the grid in the case of excess power output.

Figure 2.14. Structure of grid-connected PV power

system

27

2.4.4.3 Diesel Generator

Concerning the traditional sources seen as backup power, for small-scale microgrids the diesel

generator is the most used because of the low initial cost and simplicity. The difference

between load consumption and renewable generation causes actuations in the microgrid bus

voltage.

Thus, for off-grid operating mode or limited public grid availability a power balance is

performed by adjusting the diesel generator power and storage for voltage stabilization.

Although the diesel generator large capacity backup power can provide long-term support for

the microgrid operation [3].

A generator is one of the major components of a hybrid power system. It provides energy for

the load in the unlikely scenario that supply falls short of demand. In most cases, generators

are used to maximize the efficiency of renewable energy, to reinforce the frequent energy

deficit when power interruption occurs in renewable sources and the battery is not able to

provide the required energy. Generators are machines used to produce electricity by

transforming the kinetic energy of the motion of combustion engines into electricity through

different energy sources [29]. They are chosen according to their size, range, type, the kind of

load to be fed and the type of fuel they use to be operated.

A diesel generator is a diesel engine coupled to an electrical generator called an alternator via

a shaft to produce electrical energy. The diesel generator uses the chemical energy available

in the fuel and converts it into mechanical energy. The mechanical energy, in turn, drives the

engine shaft which is connected to the alternator. Diesel generator sets are mainly used: in

places where the electricity grid is not available, as uninterruptible backup power, as well as

in various complex applications such as peak shaving, export to the electricity grid and grid

support [30].

Diesel generators operate most efficiently when used at full load. Figure (2.15) shows a typical

efficiency curve for a generator set. It is clear that the efficiency decreases significantly as the

load decreases. In addition, when the load increases from 20 to 80 per cent, the efficiency of

the generator doubles. Thus, the fuel consumption per kWh is reduced by two times.

28

2.4.4.4 ENERGY STORAGE

ES technologies solve the imbalance between supply and demand. In distributed generation,

they solve the intermittency and uncertainty of output and load shifting. They also enable a

number of other functions such as black-start, power quality adjustment and control, and

stability [6].

ES technologies include physical, electromagnetic, electrochemical, and phase-change forms.

Physical ES technologies include pumped storage, compressed air ES (CAES) and flywheel ES;

electromagnetic ES includes superconducting magnetic ES (SMES), supercapacitor, and high-

energy density capacitor; electrochemical ES includes various types of batteries such as lead-

acid battery, nickel-hydrogen battery, nickel-cadmium battery, lithium-ion battery, sodium

sulfur battery, and flow battery; phase-change form includes ice thermal storage [6].

2.4.4.5 Battery

It is a chemical form of storing electricity and it exists in different types such as batteries based

on sodium sulfur battery, lead-acid, lithium-ion battery, vanadium redox and nickel-cadmium

battery.

1. Sodium sulfur battery: Owing to its high energy density, its size is just 1/5 of a lead-acid

battery while the efficiency is up to 80%, contributing to convenient modular design,

transportation, and installation. It can be installed by stage according to the intended purpose

and capacity, and suits urban substations and special loads. It is a promising ES technology for

Figure 2.15. Typical genset efficiency curve [31]

system

29

DG and the microgrid in improving the system stability, shifting loads, and maintaining power

supply in an emergency.

2. Lead-acid battery: Its lifetime will be reduced when working at a high temperature. Similar

to a nickel-cadmium battery, it has a low specific energy and specific power, but is

advantageous because of its low price and cost, high reliability, and mature technology and

has been widely used in electric power systems. However, it has a short lifetime and causes

environmental pollution during manufacture. It is mainly used as the power source for closing

of circuit breakers during system operation, and an independent power source for relay

protection, driver motor, communication, and emergency lighting in the event of failure of

power plants or substations.

3. Nickel-cadmium battery: It has a high efficiency and long lifetime, but the capacity

decreases as time goes by, and the charge retention needs to be enhanced. Furthermore, it

has been restricted by the EU due to heavy metal pollution. It is rarely used in electric power

systems.

4. Lithium-ion battery: It has a high specific energy and specific power, little self-discharge,

and causes no pollution. However, due to the influence of the process and difference in

ambient temperature, the system indices are more often worse than those of a cell, and in

particular, the lifetime is several times or even more than 10 times shorter than that of a cell.

What is more, integration of a high capacity is very difficult and the cost for manufacture and

maintenance very high. In spite of this, the lithium-ion battery is expected to be widely used

in DG and the microgrid thanks to advancements of technologies and reduction of costs.

5. Flow battery: Flow battery features slight electrochemical polarization, 100% discharge,

long lifetime, and rated power independent of rated capacity. The capacity can be increased

by adding electrolyte or increasing the concentration of the electrolyte. The storage form and

pattern can be designed according to the location. It is a promising ES technology for DG and

the microgrid in improving the system stability, shifting loads, and maintaining power supply

in an emergency [6].

30

2.4.5 Microgrid Monitoring

The monitoring and energy management system of the microgrid serves real-time, extensive

monitoring of distributed generation (DG), energy storage (ES), and loads within the microgrid.

In grid-connected operation, islanded operation, and during transition between operation

modes, it controls and optimizes the DG, ES, and loads, thereby ensuring secure and stable

operation of the microgrid at the maximum energy efficiency as seen in Figure (2.16).

The monitoring system coordinates with the local control and protection and remote

distribution dispatch, and has the following functions:

1. Real-time monitoring of supervisory control, data acquisition, and DG;

2. Service management: forecast of power flow (including tie line power flow, DG node power

flow, and load flow) and DG output; DG output control and power balance control;

3. Smart analysis and decision-making: optimized dispatch of energy. By collecting

information of DGs, lines, the distribution network, and loads in real time, the monitoring

system monitors the power flow across the microgrid and adjusts the operation of the

microgrid in real time based on operation constraints and energy balance constraints. In the

monitoring system, energy management is the core that integrates the DG, load, ES, and the

point of common coupling [6].

Figure 2.16. The main components of the future smart grid [29]

system

31

2.5 Smart grids

Smart grid has numerous definitions and interpretations, which depend on the specific drivers

and benefits to each utility, country, and federal goals, and the various industry stakeholders.

A preferred view of smart grid is not what it is, but what it does, and how it benefits utilities,

consumers, the environment, and the economy.

• The European Technology Platform (comprising European stakeholders and the surrounding

research community) defines smart grid as “An electricity network that can intelligently

integrate the actions of all users connected to it—generators, consumers and those that do

both, in order to efficiently deliver sustainable, economic and secure electricity supply”.

• According to the U.S. Department of Energy (DOE), “Grid 2030 envisions a fully automated

power delivery network that monitors and controls every customer and node, ensuring two-

way flow of information and electricity between the power plant and the appliance, and all

points in between”.

• The US Electric Power Research Institute (EPRI) defines smart grid as “The modernization of

the electricity delivery system so it monitors, protects, and automatically optimizes the

operation of its interconnected elements—from the central and distributed generator

through the high-voltage network and distribution system, to industrial users and building

automation systems, to energy storage installations and to end-use consumers and their

thermostats, electric vehicles, appliances, and other household devices” .

The U.S. DOE’s National Energy Technology Laboratory (NETL) established seven principal

characteristics that define the functions of smart grid as seen in Figure (2.17). Moreover, Table

(2.6) summarizes these seven characteristics and contrasts today’s grid with the vision for the

smart grid [30].

Today’s Grid Principal Characteristic Smart Grid

Consumers do not interact

with the grid and are not

widely informed and

educated on their role in

Enables consumer

participation

Full-price information

available, choose from many

plans, prices, and options to

buy and sell

32

reducing energy demand

and costs

Dominated by central

generation, very

limited distributed

generation and storage

Accommodates all

generation and storage

options

Many “plug-and-play” DERs

complement central

generation

Limited wholesale markets,

not well integrated

Enables new markets Mature, well-integrated

wholesale markets, growth

of new electricity markets

Focus on outages rather than

PQ (power quality)

Meets PQ needs PQ a priority with a variety of

quality and price options

according to needs

Limited grid intelligence is

integrated with asset

management processes

Optimizes assets and

operates efficiently

Deep integration of grid

intelligence with asset

management applications

Focus on protection of assets

following fault

Self-heals

Prevents grid disruptions,

minimizes impact, and

restores rapidly

Vulnerable to terrorists and

natural disasters

Resists attack Deters, detects, mitigates,

and restores rapidly and

efficiently

Table 2.6. DOE Seven characteristics of a Smart Grid

33

2.5.1 In What Ways Are Smart Grids ‘‘Smarter’’?

SGs are ‘‘smarter’’ in two ways. First, they have the ability to manage the two-way flow of

electricity and information to optimize supply and demand. Traditional electric grids have one-

way communication between utilities and customers: that is there is a one-way flow of

information from customers to the grid (through meters) and a one-way flow of energy from

the grid to customers. In contrast, SGs enable two-way flow of information (through a variety

of interfaces) and energy (through distributed generation and storage). This is achieved

through smart metering technologies and sensors that are installed throughout transmission

and distribution grids, and which are linked to integrated communication networks to collect

and consolidate data. This ability of two-way communication is fundamental to SG operations.

Customers, for example, can proactively monitor and manage their electricity use, and can

even sell back to the grid surplus renewable electricity that is produced at home.

Figure 2.17. Smart grid environment within the broader electricity system [29]

34

SGs are ‘‘smarter’’ also in the sense that they are capable of integrating a wide variety of

energy sources and energy customer services—which are now separately managed in

traditional power systems—in highly interconnected electricity systems. SGs also integrate a

variety of interfaces, including home energy management systems (HEMS), building energy

management systems (BEMS), and advanced metering infrastructure (AMI). SGs can

coordinate the needs and capabilities of different generators, grid operators, end users, and

electricity market stakeholders to operate all parts of the system efficiently as seen in Figure

(2.18). All these components require the integration of SGs to achieve scale benefits and cost

effectiveness [31].

2.5.2 Sensing and Measurement in Smart Grid

Innovation in sensing and measurement is fundamental for the realization of a more aware

and reliable smart grid. This objective can only be achieved by radically upgrading the sensing,

measurement, and metering throughout the grid. The smart grid will have real-time

measuring devices deployed across the power grid. These sensors will monitor the system and

Figure 2.18. The future smart Grid and its application [31]

35

provide data to enable different online and offline applications. The measuring devices

installed must be reliable and cost effective also.

These sensors can play an important role in realizing a smart grid by:

• Collecting more information in a given time interval f or analyzing the causes and

restructuring the timeline of failure.

• Detecting the potential problems comparatively early thereby helping in the generation of

a better corrective action.

• Detection of an external threat.

• Operating the grid in a more efficient way.

• Providing new services to the consumers like demand-side management [32].

2.5.3 Next Generation Smart Communication Subsystems in SGs

The term grid or power grid is used in electricity systems, which mostly refers to the

generation, transmission, distribution, and control of electrical power. But smart grid or

intelligent power grids are the penetration of communication technologies in the power grid

and commonly named as SG (see Figure (2.19)). The prime aim of the SG communication

systems is the two-way communication or information flow along with two-way power flow

between grid and the consumer. The key requirements and benefits of SG are improvement

of the quality and reliability of the power grids, improvement of capacity and efficiency, ability

to overcome the disruption automatically, automation of maintenance and operation,

handling system disturbance by incorporating self-healing and predictive maintenance,

accommodation of different power sources distributed in different geographical areas and

enabling smart energy system, smart information system and smart communication system in

the grid. In this section, the main focus will be on the communication systems in SG.

Exchange of information efficiently and reliably is the key requirements of future SG

communication systems. Some of the key requirements of SG are:

- The communication subsystems in SG must maintain the quality of service (QoS) of the

critical data and must be delivered faster and correctly.

- Since large number of different types of devices and communication technologies are used

in SG heterogeneous network, the communication subsystems in SG must be reliable.

- It must have high coverage area and in time response to any event in the SG.

- Secure and reliable data communication through SG is also a major concern of SG.

36

Communication technologies used in SG can be classified as follows:

→ Wireless communication technologies for SG.

▪ Wireless mess network

▪ Cellular communication

▪ Cognitive radio

▪ ZigBee

▪ Satellite communication

▪ Free-space optical communication

→ Wired communication technologies for SG.

▪ Fiber-optic communication

▪ Power line communication (PLC)

2.6 Conclusion

This chapter has presented updates in literature concerning the research topic, starting with

an overview about Algeria, the country of the case study then examining the main elements

of smart microgrids.

Figure 2.19. Smart cities and IoT

37

CHAPTER 3. METHODS

38

3.1 Introduction

To attain the proposed objectives of our study, this chapter discusses the appropriate

procedures that have been done while conducting the research. It addresses mainly the data

collection methods, the techniques and statistical tests used for data analysis. It also explores

the software packages utilized for data processing.

3.2 Research Approach Overview

The main objective of our study is to propose a modeled and simulated design of a simple

DC microgrid for a localized area in the “university campus”.

To achieve this goal, our research has been conducted throughout four steps:

Step 01: Demand-side management;

Step 02: Supply-side management;

Step 03: Simulation and control;

Step 04: Analysis

Before any assessment of the available data, a general brain storming was made to gather all

the needed information before being examined. The preliminary overview of the input data

and expected output data were summarized in the Table 3.1 and 3.2 respectively.

Input Data

Load profile

-Primary consumption

Weather resources

-Radiation

-Sunshine duration

-Wind speed

-Temperature

Technical parameters

-Photovoltaic

-Wind turbine

-Generator

-Energy Storage

-Converter

-Power outage

Project costs &

Finance

-Capital

-O&M

-Fuel

-Utility tariff

-Feed-in-tariff

-Depreciation

Table 3.1. Input data for the research

39

Output Data

Sizing analysis

-Optimal size of

Distributed energy

resources and storage

system

Energy analysis

-Energy production

-Efficiency and lifetime

-Reliability index

-Emissions reduction

Financial analysis

-Payback period

-Net present value

-Internal rate of return

-Annual lifecycle saving

-Lifecycle cost

Uncertainty

analysis

-Scenario analysis

-Sensitivity analysis

3.2.1 Study assumptions

A preliminary natural assessment for Chetouane’s potential shows that it has:

• A very low wind potential, with an annual mean wind speed under to 3 m/s [26]

• A very significant solar potential, with almost 1900 kwh/m2 radiation [26]

Table 3.2. Output data of the research

Figure 3.1. Wind potential assessment in Chetouane [26]

40

For that reason, our energy production will be relying on photovoltaic panels with a backup

system of batteries and a diesel generator.

3.2.2 Research procedure

Combining all the data needed for the study, and using different technical assessments, the

general overview of the research approach is described in the following scheme (Figure 3.3)

Figure 3.3 Research approach overview

Figure 3.2. Solar potential assessment in Chetouane [26]

41

3.2.3 Software Based Approach

Simulation and optimization software are the most common tools for evaluating the

performance of renewable energy systems. In computer simulation, the performance and

energy production of different system configurations are compared in order to obtain an

optimal design. Some of the best-known software packages are: MATLAB, PVsyst, HOMER,

HYBRID2, HOGA, HYDROGEMS, etc. PVsyst 7.0 was used in our research for the seizing and

analysis of the solar system while the modeling and simulation of the microgrid system was

carried out using Simulink MATLAB.

3.3 Step 01: Demand side management

3.3.1 Building description

The study is conducted for PAUWES building situated in Chetouane- Tlemcen city (see Figure

2.2). This building is used as an educational institution, in coordination with the University of

Tlemcen. The building was built in 1989, and being used by the Pan African University starting

from 2014.

PAUWES building is a two-floor structure made of concrete and steel. Its tinted glass front part

faces the northern direction. PAUWES building includes both administration offices and

classrooms. The energy end users are 22 Employers and around 120 students.

Figure 3.4. PAUWES building

42

3.3.2 Analysis of energy consumption

The energy audit gives visibility on energy consumption and cost. This means it provides us

with a comprehensive overview of all the types of energy being used. It also breaks out the

energy consumption by users so that we know where and when the energy is being consumed.

Furthermore, it describes the energy saving alternatives that could be adopted and provides

an energy management plan and easily implemented solutions.

For our case study, the data on energy consumption in the last three years were not provided.

Due to Covid-19, even a walkthrough could not be conducted. Thanks to an audit report done

by a group of students - in October, 10th, 2019, data on energy consumption were collected.

The report was validated by the professor and it was obtained by asking the users and checking

the equipment for performance details [36].

For our analysis and using Excel, the building was divided to 25 parts as following:

Figure 3.5. GPS localization of PAUWES (source: google earth)

43

1. A0

2. A1

3. A2

4. A3

5. A4

6. A5

7. A6

8. A7

9. Interview room

10. Hall 1

11. Toilet Men

12. Stairs

13. Hall 2

14. Toilet Women

15. Students Affaires

16. E-Library

17. Information

18. Coordinators

19. B7 Research.

20. Deputy Director

21. Kitchen

22. Finance

23. Secretariat

24. Director

25. Meeting Room

The Appliances were identified and classified into the following sections:

• Laptops + Desktops + Projectors

• Air Conditioning

• Lighting

• Office Equipment

• Kitchen Appliances

• Others

The consumption of each part was estimated by calculating the usage of each appliance

(On/Idle) and thus, the Total power of the load was determined as:

𝑃𝑡𝑜𝑡𝑎𝑙 = ∑ 𝑃𝑖 = ∑[(ℎ𝑜𝑛 . 𝑝𝑜𝑛)(ℎ𝐼𝑑𝑙𝑒. 𝑝𝐼𝑑𝑙𝑒)]𝑖

25

𝑖=1

25

𝑖=1

Where:

44

Ptotal : Load

Pi : Power consumed per part

hon : Operation time of the appliance

pon : power consumption when the device is ON Mode

hIdle : Idle time of the appliance

pon : power consumption when the device is Idle Mode

The PAUWES building has a number of different uses and includes offices, teaching rooms,

halls, laboratories and a kitchen. The energy data were estimated and divided into two cases

related to the energy needs during a working day and a weekend/vacation time respectively.

3.4 Step 02: Supply-side management

3.4.1 System configuration

Figure (3.6) illustrates the microgrid considered in our study. It is a grid-connected DC

microgrid consisting of a PV module, diesel generator, storage system, inverters, switches and

controllable loads. More details of each part are explained and given in the next sections.

Figure 3.6. System configuration

45

3.4.2 System sizing

Before starting the dimensioning of our solar system, we had to determine the main

constraints of the project and use these constraints as a starting point for the design, among

which we can find:

1- Building a system within a target budget;

2- Assessing the appropriate location for the best exposure to the sun;

3- Evaluating the effectiveness of products and technologies;

4- Designing a system that compensates for a certain percentage of our energy consumption;

5- Conceiving a system that takes up as little space as possible and susceptible for a future

expansion.

It was from 4 and 5 that we approached the dimensioning of the project, using PVsyst

software.

The surface available was estimated using google earth software and it had the value of

around 600 m2 and the average daily consumption is 15 kwh

Solar panels work best when they are oriented directly towards the sun. But this is

complicated because the sun moves across the sky throughout the day. It also changes its

Figure 3.7. Building’s Surface estimate

46

angle in the sky with the seasons. Trackers automatically adjust the system so that the panels

always face the sun, but since trackers are often too expensive, it is better to buy more panels

rather than using trackers.

For an optimum orientation, in our location - the Northern Hemisphere-, experts [37]

recommend that the panels should:

- Face the south: for the Azimuth angle

- Set them at a tilt angle that is equal to our latitude: 34° shown in Figure (3.8).

We can make some seasonal adjustments to get more power by changing the tilt angle:

In summer, latitude minus 15°. In winter, latitude plus 15°.

3.4.2.1 Geographical site

By Defining the geographical parameters of our site with PVsyst software, entering the

geographical coordinates for our building:

• Latitude: 34.9213°

• Longitude: -1.2951°

• Altitude: 582 m

Figure 3.8. Panels orientation Figure 3.9. System’s simplified sketch

47

We get the solar paths graph illustrated in Figure (3.11)

3.4.2.2 Natural resources assessment and weather data

In a chosen region, the total radiation, sunshine duration and temperature as measured data

are required to generate electricity with a photovoltaic panel.

Therefore, the monthly measurement data in Chetouane - Tlemcen were collected and they

are shown in Table (3.3) The table shows that the value of the average monthly radiation

measured is 150 kWh/m2 the value of the average annual temperature is 15.7°C. Thus, it is

clear that Tlemcen has a large potential for solar energy.

Figure 3.10. Defining the site’s geographical position

Figure 3.11. Solar paths at Chetouane

48

3.4.2.3 Defining Solar system components

• PV Module

The characteristics of the selected PV module are summarized in the following tables:

Table 3.3. Weather data for Chetouane

49

PV module Si-poly Model TSM-300PE14A

Manufacturer Trina Solar Original PVsyst database

Number of PV modules In series 17 modules, In parallel 3 strings

Total number of PV modules nb. modules 51

Unit Nom. Power 300 Wp

Array global power Nominal (STC) 15.30 kWp

At operating cond. 13.73 kWp (50°C)

Array operating characteristics (50°C) U mpp 553 V

I mpp 25 A

Total area Module area 99.0 m²

Cell area 89.4 m²

Table 3.4. PV System sizing and characteristics

Figure 3.12. Relation of I-V/P-Vo f PV cell at different light intensities.

(a) (b)

50

The output voltage and current of the photovoltaic cells vary according to light intensity and

temperature. Figure (3.12) shows an example of the relationship between current and voltage

(a) and the relationship between power and voltage (b) of PV at different light intensities.

Figure (3.13) shows an example of the relationship between current and voltage (a) and

between power and voltage (b) of PV cells at different temperatures. At a certain light

intensity and temperature, the PV cell can operate at a different voltage, whereas at only a

certain voltage, the output power of the PV cell reaches the maximum efficiency. Photovoltaic

production uses MPPT voltage control to control the photovoltaic cell operates at the voltage

point of maximum output power.

• Inverters

To convert DC voltage to AC voltage or vice versa, an inverter must be used. This compensates

for power failures and stabilizes the electrical voltage. PVsyst offers several inverter

technologies depending on the type of power supply system; there are grid-connected

inverters that can connect the DC PV to the AC grid and bidirectional inverters that can

connect between the PV generator and/or batteries and the AC load.

In our case, we select an inverter that can be found in the library has the following

characteristics:

Figure 3.13. Relation of I-V/P-Vo f PV cell at different Temperatures.

(a) (b)

51

Inverter Model Conext TL 10000 E

Manufacturer Schneider ElectricOriginal PVsyst database

Unit Nom. Power 10.00 kWac

Oper. Voltage 100-850

Inverter pack Total power 15.0 kWac, Pnom ratio 1.02

Nb. of inverters 3

Total Total power 15 kWac, Pnom ratio 1.02

• Storage system

For our microgrid, we choose a Li-ion battery with 14V and 100 Ah, a Generic from PVsyst

library that has the below mentioned specifications:

Battery Model Li-Ion, 14V 100 Ah

Manufacturer Generic

Nb. of units 5 in series

Voltage 64 V

Nominal Capacity 103 Ah (C10)

Discharging min SOC 20.0%

Stored energy 5.3 kWh

Temperature Fixed (25°C)

Table 3.5 Inverter’s characteristics

52

Battery input charger Model Generic

Max. charging power 3.0 kWdc

Battery to Grid inverter Model Generic

Max. discharging power 2.0 kWac

• Diesel Generator

The selected one is a MTU 4R0113 DS63 Diesel Generator Set, produced by EVECO with the

benefits of a low fuel consumption, emissions optimizations available, high availability and

reliability and long maintenance intervals. The technical characteristics are summarized in the

table below [39]:

Table 3.6 Battery’s characteristics

Table 3.7 genset’s characteristics

53

3.5 Step 03: Simulation and control

The operation of the various components of the microgrid were analyzed using

MATLAB/Simulink. Simulink has an environment called Simscape that can be used to model

dynamic systems. The Simscape demonstrates its strength in physical modelling using

equation-based representations for solar modules, batteries, converters, diesel generator and

a charge controller.

3.5.1 Load profile

In our simulation, we are taking load profile for a working day as it is represented in Figure

(3.14)

3.5.2 PV block

The PV model is constructed using Matlab/Simulink to illustrate and verify the non-linear I-V

and P-V output characteristics of the PV module.

Figure 3.14. Load profile modeling

54

The example day for simulation was the 11/05/2020 where the input data of irradiation were collected

from [40]

3.5.3 Storage system block

The demand for electricity fluctuates according to the time of day and the time of year. Since

the traditional electricity grid is not able to store electricity, the mismatch between supply and

demand is more likely to be observed. As the concept of microgrid becomes more and more

widespread, energy storage is advantageous in the management of such a system. A desired

0

200

400

600

800

1000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

W/

m2

hour

Irradiation

Figure 3.15. PV model block

Figure 3.16. Daily irradiation for May,11th 2020

55

form of energy storage should provide the electricity to the grid and store enough energy for

low electricity consumption.

The short-term storage that is studied and modelled in our case is: batteries storage.

There are several approaches to modelling a battery. In our case, Simulink implements a set

of predetermined charging behaviors for four types of batteries: lead-acid, lithium-ion, nickel-

cadmium and nickel-metal hydride. Figure (3.17) illustrates a detailed modelling of the charge

and discharge battery in MATLAB/Simulink.

3.5.4 Diesel generator block

The diesel engine model provides a description of the fuel consumption rate as a function of

the speed and mechanical power output of the engine, and is generally modelled by a simple

first-order model relating fuel consumption to the mechanical power of the engine. The

output power of the engine and generator varies with load to meet demand.

The governor can be defined as a mechanical or electromechanical device for controlling the

speed of an engine by relating the fuel intake, [13]. The task of the governor is to adjust the

fuel flow and then regulate the input to the engine and generator, allowing the power

required to respond to load variation. There are several types of governors, such as

Figure 3.17. Battery model block

56

mechanical, electronic, microprocessor-based and others. Figure (3.18) illustrates the diesel

engine model in Matlab/Simulink.

3.5.5 Global configuration of the microgrid

After being implemented in Matlab/Simulink, the models are integrated in combination to

form a Micro-Grid system (off/on grid) as shown in Figure (3.19)

Figure 3.18. Diesel generator model block

Figure 3.19. General block of the microgrid

57

The charts presented in the Figure (3.20) and (3.21) propose the control algorithms for the

microgrid operation during peak load periods for two cases: sufficient PV power outage and

insufficient PV power.

Figure 3.20. Algorithm control in case of PV availability

Figure 3.21. Algorithm control in case of PV non availability

58

3.6 Step 04: Analysis

Using PVsyst an economical and environmental analysis were conducted for the solar system

(panels + batteries). The results will be found in the chapter 4.

The Assumptions for the economic study are shown in the Table (3.8) below:

Item Cost per unit

Panels 300 $

inverter 100 $

Battery 1400 $

Taxes 2%

O&M 320 $

Inflation 0.2 %

Discount rate 0.5 %

Subsidies 1000 $

Project lifetime 25 years

3.7 Conclusion

This chapter addressed in details the methods and approaches carried out throughout the

research process, from data collection to simulation passing by the sizing and analysis. The

results and discussion will be presented in the next chapter.

Table 3.8 Economical Data for analysis

59

CHAPTER 4. RESULTS AND DISCUSSION

60

4.1 Introduction

Following our research approach, in this section the results and their discussion will be

presented in by the following order:

Step 01: Demand-side management;

Step 02: Supply-side management;

Step 03: Simulation and control;

Step 04: Analysis.

4.2 Step 01: Demand-side management

Load profiling and categorization

Once the load details were collected, load profiling is performed to determine the maximum

load, the average daily daytime energy demand for both working day and a weekend time,

the average yearly energy demand and an analysis for energy consumption per part and

appliance.

• The Figure (4.1) shows the daily load curve for a working day and a weekend day.

The peak load of 37 kWh is observed in the beginning of both the morning and afternoon

periods, and it can be explained by the activity of both administration and students during

those rush hours. From 11 to 13:00 AM, lunch time shows a decrease in the consumption.

For a weekend day the consumption decreases very clearly except for the permanent

appliances such as the sever and refrigerators etc.

61

• The Figures (4.2) and (4.3) represent the electricity daily consumption for the whole

building corresponding to its different zones for both a working day and a weekend

day respectively. The energy consumption for a working day reaches 350 kWh while it

doesn’t exceed 88 kWh in a non-working day.

• Figure (4.4) shows the yearly energy consumption of the building which is estimated

by almost 82 GWh. It can be seen in the three figures that that Hall 2 has a high

consumption compared to the rest of the building. The reason for this is the presence

of the server in the area.

Figure 4.1. Daily load curve for both a working and a weekend day

Figure 4.2. Daily average consumption per part for a working day

62

Figure 4.3. Daily average consumption per part for a weekend day

Figure 4.4. Yearly average consumption per part

63

• The charts in Figures (4.5) and (4.6) display the electricity distribution consumption in

the building according to its different uses for both daily and yearly period respectively.

It can be seen that office equipment has a significant consumption compared to the rest.

Air-conditioning comes in second place with a small difference with the energy

consumption related to the use of laptops and related equipment, while lighting comes

last in relation to the rest, but its consumption is still very high in general.

Figure 4.5. Daily consumption by appliance for a working day

Figure 4.6. Yearly Distribution of consumed energy

64

4.3 Step 02: Supply-side management

Analyzing the values of the daily measurement of both temperature and irradiation (average

radiation measured monthly is 150 kWh/m2, annual average temperature is 15.7°C) shows

that Tlemcen has a significant potential for PV.

Our system is composed of 51 Monocrystalline silicon solar panel of 300 W peak power. The

data acquisition system and PVsyst software tools used in this study can import

meteorological which be used to estimate the amount of energy produced.

The photovoltaic system will be installed on the PAUWES building's flat roof. The inclination

of each photovoltaic panel is at 34°, which represents the optimal angle for the whole year,

the total covered surface area is approximately 100 m2.

The output energy of photovoltaic is plotted for each month as shown in Figure (4.7.a) and

Figure (4.7.b). The maximum power generation are reached during summer while in winter

the electricity generated decreases but remains very important.

The total power installed by this system accounts for 24 MWh yearly which is dispatched to

the end user or grid reinjection. In determining total electricity generated of a PV system, it

has been taken to consideration all types of losses as PV and module loss, inverter loss, and

external transform as illustrated in Figure (4.8).

Figure 4.7. Yearly Distribution of produced energy

(a) (b)

65

Figure 4.8. Loss diagram

66

4.4 Step 03: Simulation and control

4.4.1 PV

The irradiation curve is given in Figure (4.9.a) while the PV output power is illustrated in Figure

(4.9.b), as seen from the figures the energy produced is a function of the irradiance received

in a determined time. Thus, as seen from the Figures (4.10.a & b), the irradiance curve also

includes cloud effects which affects directly the PV output.

(a) (b)

(b) (a)

Figure 4.9. Simulation result for PV power in a sunny day

Figure 4.10. Simulation result for PV power in a sunny day with a shading

67

4.4.2 Battery

• Charging mode

When the load is connected to the main grid, and while the solar power is available. The

batteries start charging till reaching 90% SOC, that can be seen in the Figure (4.11.a). The

voltage output of the battery shown in Figure (4.11.b) is controlled by an PI controller to be

working in within the nominal voltage.

• Discharging mode

Figure (4.12.a) shows that once the system is islanded, the batteries start discharging as soon

as power is needed while its voltage remain controlled as illustrated in Figure (4.12.b).

Figure 4.11. Simulation results for batteries charging mode

Figure 4.12 Simulation results for batteries discharging mode

(a)

(a) (b)

(b)

68

4.4.3 Microgrid

We modelled the microgrid components and build them up them into a distributed power

system using simscape power system blocks for a desktop simulation.

Subjecting this microgrid to certain dynamic disturbances:

- The first one, involves opening the circuit breaker and isolating this microgrid from the

main power grid, which means it will be completely disconnected;

- And then at the second disturbance we see when the load has reached its maximum.

The diesel generator will try to maintain the stability of the whole, it will try to maintain a

uniform frequency and voltage, while the solar photovoltaic system will follow the irradiation,

so that its energy production will change over time and our energy storage system, in this

case, will be charged to be used when the energy is needed.

On the scope illustrated in Figure (4.13), we can see the resulting outputs of the frequency

disturbances that have occurred due to the islanding of this micro-grid and then, due to this

peak load, we can see how the distributed resources change over time depending on how this

microgrid is currently operating.

Figure 4.13. Simulation results for the microgrid

69

4.5 Step 04: Analysis

4.5.1 Economic analysis of PV system

In PVsyst, after defining some economic data before starting the simulation, the results

estimated the solar system installation (PV+ batteries) costs by 26 069 USD with a LCOE of

0.226 USD/kWh and a payback period of 15.4 years. Table (4.1) shows a detailed economic

result and we can see that starting from 2036, the system will start getting net profit.

The economic analysis carried out to assess the profitability shows that the cost of the

investment can be recoverable throughout the life cycle. As seen from the Figure (4.12) the

income allocation shares 81% of net profit during the project life.

Table 4.1. Detailed economic results (USD)

Figure 4.14 Income allocation on the project life

70

4.5.2 Environmental analysis of PV system

According to the analysis of emissions by PVsyst, the designed solar system will save

approximately 242 tCO2 as balance over the lifetime of the project (25 years). As shown in

Figure (4.15), the emissions generated by the system, especially during the production and

transport of the solar system components, are offset from the seventh year of the project's

lifetime to save at the end of the project that important amount of emissions.

4.6 Conclusion

This chapter presented the results obtained during the work’s procedure. It examined the

findings with explanations and comments. Further conclusions are addressed in the next

chapters.

Figure 4.15 Balance of CO2 emissions

71

CHAPTER 5. SUMMARY, CONCLUSIONS & PERSPECTIVES

72

The main aim of this study was to propose a microgrid system for the energy supply of the

PAUWES building located on the campus of Chetouane University in Tlemcen, Algeria.

The first was a literature review to investigate the potential of energy resources and to identify

the possible energy sources that could be used for energy production. As this study focuses

on the potential of solar energy, local meteorological data such as annual changes in solar

radiation and temperature were required. The hybrid system covered by this study consists of

different technologies for energy production, processing and storage. These system

components are photovoltaic panels, diesel generators and batteries connected to the main

grid. Extensive research has been carried out to determine the optimum size and technical

performance using PVsyst software. The hybrid system was then modelled using Simulink

MATLAB to evaluate the various energy management strategies. Finally, an economic and

environmental analysis of the solar system was carried out in order to examine the benefits

of adopting this technology.

During the analysis of the results, the following conclusions could be drawn:

✓ Ensuring a sustainable energy system and saving energy relies on balancing both

production and consumption. The production side can be conducted through technical

assessments while the end user attitudes affect also the consumption therefore

awareness among users and small gestures like switching off lights or using automatic

shutdown printers are of an important recommendation.

✓ Tlemcen region has an important potential for solar energy, and this potential is only

exclusive to the northern part of the country, let alone the rest of the country, the

Sahara where held the highest irradiation in the word are held.

✓ Nowadays, the energy produced by the proposed system isn’t cost effective compared

to the cheap electricity generated traditionally by burning fossil fuels mainly natural

gas. Those prices are heavily subsidized by the government.

✓ The system adopted in this research goes along with the Algerian and global energy

action plan by implementing renewables into the energy mix.

73

✓ Given the intermittent nature of renewable sources, the main problem associated with

stand-alone systems is the continuity of service. This explains why energy storage and

conventional sources are required. This energy mix can be a solution in itself while the

development of new technologies is still a challenge.

While the focus of this work has covered a variety aspect of microgrid, the thing that made

it difficult in the context of a master project to assess each aspect in details from sizing to

modeling and from simulation to analysis. This work can serve as a basis for various future

works. The latter may focus on different aspects:

✓ Other renewable energy sources, such as wind power, would be combined with

existing solar energy to ensure that the renewable fraction is maximized and

carbon dioxide emissions are emphasized to a minimum.

✓ The microgrid can be extended to feed the entire campus, and with further

detailed assessments and studies, it can be adopted in reality and implemented in

the field.

✓ With regard to system energy management and control, other smart monitoring

options could be developed and explored for better energy production, conversion

and storage.

74

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Documents

MODELING, SIMULATION AND SIZING OF A MICROGRID IN THE